SUMMARYThe nervous system evolved to coordinate flexible goal-directed behaviors by integrating interoceptive and sensory information. Hypothalamic Agrp neurons are known to be crucial for feeding behavior. Here, however, we show that these neurons also orchestrate other complex behaviors in adult mice. Activation of Agrp neurons in the absence of food triggers foraging and repetitive behaviors, which are reverted by food consumption. These stereotypic behaviors that are triggered by Agrp neurons are coupled with decreased anxiety. NPY 5 receptor signaling is necessary to mediate the repetitive behaviors after Agrp neuron activation while having minor effects on feeding. Thus, we have unmasked a functional role for Agrp neurons in controlling repetitive behaviors mediated, at least in part, by neuropeptidergic signaling. The findings reveal a new set of behaviors coupled to the energy homeostasis circuit and suggest potential therapeutic avenues for diseases with stereotypic behaviors.

Mice emit ultrasonic vocalizations (USV) that communicate socially-relevant information. To detect and classify these USVs, here we describe VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect USVs in audio files, eliminating the need for user-defined parameters. VocalMat also uses computational vision and machine learning methods to classify USVs into distinct categories. In a dataset of >4,000 USVs emitted by mice, VocalMat detected over 98% of manually labeled USVs and accurately classified ~86% of the USVs out of eleven USV categories. We then used dimensionality reduction tools to analyze the probability distribution of USV classification among different experimental groups, providing a robust method to quantify and qualify the vocal repertoire of mice. Thus, VocalMat makes it possible to perform automated, accurate, and quantitative analysis of USVs without the need for user inputs, opening the opportunity for detailed and high-throughput analysis of this behavior.

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Increasing age is the strongest predictor of risk of COVID-19 severity and mortality. Immunometabolic switch from glycolysis to ketolysis protects against inflammatory damage and influenza infection in adults. To investigate how age compromises defense against coronavirus infection, and whether a pro-longevity ketogenic-diet (KD) impacts immune-surveillance, we developed an aging model of natural murine beta coronavirus (mCoV) infection with mouse hepatitis virus strain-A59 (MHV-A59). When inoculated intranasally, mCoV is pneumotropic and recapitulates several clinical hallmarks of COVID-19 infection. Aged mCoV-A59-infected mice have increased mortality and higher systemic inflammation in the heart, adipose tissue and hypothalamus, including neutrophilia and loss of γδ T cells in lungs. Activation of ketogenesis in aged mice expands tissue protective γδ T cells, deactivates the NLRP3 inflammasome and decreases pathogenic monocytes in lungs of infected aged mice. These data establish harnessing of the ketogenic immunometabolic checkpoint as a potential treatment against coronavirus infection in the aged.